Merge pull request #203 from zivid/2025-06-13-update-python-samples

Samples: Automatic updates to public repository

Author: zividgerman

README.md

@@ -63,6 +63,8 @@ from the camera can be used.
           - [camera\_user\_data](https://github.com/zivid/zivid-python-samples/tree/master/source/camera/info_util_other/camera_user_data.py) - Store user data on the Zivid camera.
           - [capture\_with\_diagnostics](https://github.com/zivid/zivid-python-samples/tree/master/source/camera/info_util_other/capture_with_diagnostics.py) - Capture point clouds, with color, from the Zivid camera,
             with settings from YML file and diagnostics enabled.
+          - [context\_manager\_with\_zivid](https://github.com/zivid/zivid-python-samples/tree/master/source/camera/info_util_other/context_manager_with_zivid.py) - Sample showing how to use a context manager with Zivid
+            Application and safely return processed data.
           - [firmware\_updater](https://github.com/zivid/zivid-python-samples/tree/master/source/camera/info_util_other/firmware_updater.py) - Update firmware on the Zivid camera.
           - [frame\_info](https://github.com/zivid/zivid-python-samples/tree/master/source/camera/info_util_other/frame_info.py) - Read frame info from the Zivid camera.
           - [get\_camera\_intrinsics](https://github.com/zivid/zivid-python-samples/tree/master/source/camera/info_util_other/get_camera_intrinsics.py) - Read intrinsic parameters from the Zivid camera (OpenCV

modules/pyproject.toml

@@ -18,8 +18,9 @@ dependencies = [
     "matplotlib",
     "nptyping",
     "numpy",
-    "open3d; python_version <= '3.11'",
+    "open3d",
     "opencv-python",
+    "pandas",
     "pyyaml",
     "pyqt5-sip==12.15.0",
     "pyqt5",

modules/zividsamples/gui/stitch_gui.py

@@ -8,37 +8,29 @@
 
 """
 
-import sys
 from pathlib import Path
 from typing import Dict, List, Optional
 
 import numpy as np
 import zivid
 from PyQt5.QtCore import pyqtSignal
 from PyQt5.QtGui import QImage
-from PyQt5.QtWidgets import QHBoxLayout, QMessageBox, QPushButton, QVBoxLayout, QWidget
+from PyQt5.QtWidgets import QHBoxLayout, QPushButton, QVBoxLayout, QWidget
 from zividsamples.gui.capture_at_pose_selection_widget import CaptureAtPose, CaptureAtPoseSelectionWidget
 from zividsamples.gui.hand_eye_configuration import HandEyeConfiguration
+from zividsamples.gui.pointcloud_visualizer import Open3DVisualizerWidget
 from zividsamples.gui.pose_widget import PoseWidget, PoseWidgetDisplayMode
 from zividsamples.gui.robot_control import RobotTarget
 from zividsamples.gui.rotation_format_configuration import RotationInformation
 from zividsamples.transformation_matrix import TransformationMatrix
 
-if sys.version_info < (3, 12):
-    from zividsamples.gui.pointcloud_visualizer import Open3DVisualizerWidget
-
 
 class StitchGUI(QWidget):
     data_directory: Path
     use_robot: bool
     qimage_rgba: Optional[QImage] = None
     hand_eye_configuration: HandEyeConfiguration
-    if sys.version_info < (3, 12):
-        point_cloud_widget: Optional[Open3DVisualizerWidget] = None
-        show_warning_once: bool = False
-    else:
-        point_cloud_widget = None
-        show_warning_once: bool = True
+    point_cloud_widget: Optional[Open3DVisualizerWidget] = None
     has_detection_result: bool = False
     has_confirmed_robot_pose: bool = False
     instructions_updated: pyqtSignal = pyqtSignal()
@@ -141,21 +133,7 @@ def stop_3d_visualizer(self):
 
     def start_3d_visualizer(self):
         self.stop_3d_visualizer()
-        if sys.version_info < (3, 12):
-            self.point_cloud_widget = Open3DVisualizerWidget()
-        elif self.show_warning_once:
-            folder_path = self.capture_at_pose_selection_widget.directory
-            QMessageBox.warning(
-                self,
-                "Visualization",
-                f"""\
-Visualizing the point cloud requires Python 3.11 or earlier.
-
-All transformed captures will be saved as .ply files in the folder:
-
-{folder_path.as_posix()}""",
-            )
-            self.show_warning_once = False
+        self.point_cloud_widget = Open3DVisualizerWidget()
         self.update_stitched_view()
 
     def hand_eye_configuration_update(self, hand_eye_configuration: HandEyeConfiguration):

source/applications/advanced/auto_2d_settings.py

@@ -132,12 +132,11 @@ def _find_white_mask_and_distance_to_checkerboard(camera: zivid.Camera) -> Tuple
     """
     try:
         frame = zivid.calibration.capture_calibration_board(camera)
-
         checkerboard_pose = zivid.calibration.detect_calibration_board(frame).pose().to_matrix()
         distance_to_checkerboard = checkerboard_pose[2, 3]
-
-        rgb = frame.point_cloud().copy_data("rgba_srgb")[:, :, :3]
+        rgb = frame.point_cloud().copy_data("rgba_sgrb")[:, :, :3]
         white_squares_mask = find_white_mask_from_checkerboard(rgb)
+
     except RuntimeError as exc:
         raise RuntimeError("Unable to find checkerboard, make sure it is in view of the camera.") from exc
 

source/applications/advanced/create_depth_map.py

@@ -64,25 +64,28 @@ def _visualize_and_save_image(image: np.ndarray, image_file: str, title: str) ->
 
 
 def _main() -> None:
-    with zivid.Application():
-        data_file = get_sample_data_path() / "Zivid3D.zdf"
-        print(f"Reading ZDF frame from file: {data_file}")
-        frame = zivid.Frame(data_file)
-        point_cloud = frame.point_cloud()
+    # Application class must be initialized before using other Zivid classes.
+    app = zivid.Application()  # noqa: F841  # pylint: disable=unused-variable
 
-        print("Converting to BGR image in OpenCV format")
-        bgr = _point_cloud_to_cv_bgr(point_cloud)
+    data_file = get_sample_data_path() / "Zivid3D.zdf"
+    print(f"Reading ZDF frame from file: {data_file}")
 
-        bgr_image_file = "ImageRGB.png"
-        print(f"Visualizing and saving BGR image to file: {bgr_image_file}")
-        _visualize_and_save_image(bgr, bgr_image_file, "BGR image")
+    frame = zivid.Frame(data_file)
+    point_cloud = frame.point_cloud()
 
-        print("Converting to Depth map in OpenCV format")
-        z_color_map = _point_cloud_to_cv_z(point_cloud)
+    print("Converting to BGR image in OpenCV format")
+    bgr = _point_cloud_to_cv_bgr(point_cloud)
 
-        depth_map_file = "DepthMap.png"
-        print(f"Visualizing and saving Depth map to file: {depth_map_file}")
-        _visualize_and_save_image(z_color_map, depth_map_file, "Depth map")
+    bgr_image_file = "ImageRGB.png"
+    print(f"Visualizing and saving BGR image to file: {bgr_image_file}")
+    _visualize_and_save_image(bgr, bgr_image_file, "BGR image")
+
+    print("Converting to Depth map in OpenCV format")
+    z_color_map = _point_cloud_to_cv_z(point_cloud)
+
+    depth_map_file = "DepthMap.png"
+    print(f"Visualizing and saving Depth map to file: {depth_map_file}")
+    _visualize_and_save_image(z_color_map, depth_map_file, "Depth map")
 
 
 if __name__ == "__main__":

source/applications/advanced/downsample.py

@@ -34,38 +34,40 @@ def _options() -> argparse.Namespace:
 
 
 def _main() -> None:
-    with zivid.Application():
-        user_options = _options()
-        data_file = user_options.zdf_path
+    # Application class must be initialized before using other Zivid classes.
+    app = zivid.Application()  # noqa: F841  # pylint: disable=unused-variable
 
-        print(f"Reading ZDF frame from file: {data_file}")
-        frame = zivid.Frame(data_file)
+    user_options = _options()
+    data_file = user_options.zdf_path
 
-        point_cloud = frame.point_cloud()
-        xyz = point_cloud.copy_data("xyz")
-        rgba = point_cloud.copy_data("rgba_srgb")
+    print(f"Reading ZDF frame from file: {data_file}")
+    frame = zivid.Frame(data_file)
 
-        print(f"Before downsampling: {point_cloud.width * point_cloud.height} point cloud")
+    point_cloud = frame.point_cloud()
+    xyz = point_cloud.copy_data("xyz")
+    rgba = point_cloud.copy_data("rgba_sgrb")
 
-        display_pointcloud(xyz, rgba[:, :, 0:3])
+    print(f"Before downsampling: {point_cloud.width * point_cloud.height} point cloud")
 
-        print("Downsampling point cloud")
-        print("This does not modify the current point cloud but returns")
-        print("the downsampled point cloud as a new point cloud instance.")
-        downsampled_point_cloud = point_cloud.downsampled(zivid.PointCloud.Downsampling.by2x2)
+    display_pointcloud(xyz, rgba[:, :, 0:3])
 
-        print(f"After downsampling: {downsampled_point_cloud.width * downsampled_point_cloud.height} point cloud")
+    print("Downsampling point cloud")
+    print("This does not modify the current point cloud but returns")
+    print("the downsampled point cloud as a new point cloud instance.")
+    downsampled_point_cloud = point_cloud.downsampled(zivid.PointCloud.Downsampling.by2x2)
 
-        print("Downsampling point cloud (in-place)")
-        print("This modifies the current point cloud.")
-        point_cloud.downsample(zivid.PointCloud.Downsampling.by2x2)
+    print(f"After downsampling: {downsampled_point_cloud.width * downsampled_point_cloud.height} point cloud")
 
-        xyz_donwsampled = point_cloud.copy_data("xyz")
-        rgba_downsampled = point_cloud.copy_data("rgba_srgb")
+    print("Downsampling point cloud (in-place)")
+    print("This modifies the current point cloud.")
+    point_cloud.downsample(zivid.PointCloud.Downsampling.by2x2)
 
-        print(f"After downsampling: {point_cloud.width * point_cloud.height} point cloud")
+    xyz_donwsampled = point_cloud.copy_data("xyz")
+    rgba_downsampled = point_cloud.copy_data("rgba_srgb")
 
-        display_pointcloud(xyz_donwsampled, rgba_downsampled[:, :, 0:3])
+    print(f"After downsampling: {point_cloud.width * point_cloud.height} point cloud")
+
+    display_pointcloud(xyz_donwsampled, rgba_downsampled[:, :, 0:3])
 
 
 if __name__ == "__main__":

source/applications/advanced/gamma_correction.py

@@ -46,10 +46,10 @@ def _capture_bgr_image(camera: zivid.Camera, gamma: float) -> np.ndarray:
     settings_2d.processing.color.gamma = gamma
 
     print("Capturing 2D frame")
-    with camera.capture_2d(settings_2d) as frame_2d:
-        image = frame_2d.image_bgra_srgb()
-        bgra = image.copy_data()
-        return bgra[:, :, :3]
+    frame_2d = camera.capture_2d(settings_2d)
+    image = frame_2d.image_bgra_srgb()
+    bgra = image.copy_data()
+    return bgra[:, :, :3]
 
 
 def _combine_images(image_one: np.ndarray, image_two: np.ndarray) -> np.ndarray:

source/applications/advanced/get_checkerboard_pose_from_zdf.py

@@ -65,26 +65,29 @@ def _visualize_checkerboard_point_cloud_with_coordinate_system(
 
 
 def _main() -> None:
-    with zivid.Application():
-        data_file = get_sample_data_path() / "CalibrationBoardInCameraOrigin.zdf"
-        print(f"Reading ZDF frame from file: {data_file}")
-        frame = zivid.Frame(data_file)
-        point_cloud = frame.point_cloud()
-
-        print("Detecting checkerboard and estimating its pose in camera frame")
-        camera_to_checkerboard_transform = zivid.calibration.detect_calibration_board(frame).pose().to_matrix()
-        print(f"Camera pose in checkerboard frame:\n{camera_to_checkerboard_transform}")
-
-        transform_file_name = "CameraToCheckerboardTransform.yaml"
-        print(f"Saving detected checkerboard pose to YAML file: {transform_file_name}")
-        transform_file_path = Path(__file__).parent / transform_file_name
-        assert_affine_matrix_and_save(camera_to_checkerboard_transform, transform_file_path)
-
-        print("Visualizing checkerboard with coordinate system")
-        checkerboard_point_cloud = _create_open3d_point_cloud(point_cloud)
-        _visualize_checkerboard_point_cloud_with_coordinate_system(
-            checkerboard_point_cloud, camera_to_checkerboard_transform
-        )
+    # Application class must be initialized before using other Zivid classes.
+    app = zivid.Application()  # noqa: F841  # pylint: disable=unused-variable
+
+    data_file = get_sample_data_path() / "CalibrationBoardInCameraOrigin.zdf"
+    print(f"Reading ZDF frame from file: {data_file}")
+
+    frame = zivid.Frame(data_file)
+    point_cloud = frame.point_cloud()
+
+    print("Detecting checkerboard and estimating its pose in camera frame")
+    camera_to_checkerboard_transform = zivid.calibration.detect_calibration_board(frame).pose().to_matrix()
+    print(f"Camera pose in checkerboard frame:\n{camera_to_checkerboard_transform}")
+
+    transform_file_name = "CameraToCheckerboardTransform.yaml"
+    print(f"Saving detected checkerboard pose to YAML file: {transform_file_name}")
+    transform_file_path = Path(__file__).parent / transform_file_name
+    assert_affine_matrix_and_save(camera_to_checkerboard_transform, transform_file_path)
+
+    print("Visualizing checkerboard with coordinate system")
+    checkerboard_point_cloud = _create_open3d_point_cloud(point_cloud)
+    _visualize_checkerboard_point_cloud_with_coordinate_system(
+        checkerboard_point_cloud, camera_to_checkerboard_transform
+    )
 
 
 if __name__ == "__main__":

source/applications/advanced/hand_eye_calibration/pose_conversions.py

@@ -82,8 +82,8 @@ class Representations:
     """Class to hold various transformation representations."""
 
     axis_angle: AxisAngle = AxisAngle()
-    rotation_vector: np.ndarray = np.zeros(3)
-    quaternion: np.ndarray = np.zeros(4)
+    rotation_vector: np.ndarray = field(default_factory=lambda: np.zeros(3))
+    quaternion: np.ndarray = field(default_factory=lambda: np.zeros(4))
     rotations: list = field(default_factory=list)
 
 
@@ -216,51 +216,53 @@ def print_header(txt: str) -> None:
 
 
 def _main() -> None:
-    with zivid.Application():
-        np.set_printoptions(precision=4, suppress=True)
-        print_header("This example shows conversions to/from Transformation Matrix")
-
-        transformation_matrix = load_and_assert_affine_matrix(get_sample_data_path() / "RobotTransform.yaml")
-        print(f"Transformation Matrix:\n{transformation_matrix}")
-
-        # Extract Rotation Matrix and Translation Vector from Transformation Matrix
-        rotation_matrix = transformation_matrix[:3, :3]
-        translation_vector = transformation_matrix[:-1, -1]
-        print(f"Rotation Matrix:\n{rotation_matrix}")
-        print(f"Translation Vector:\n{translation_vector}")
-
-        ###
-        # Convert from Zivid to Robot (Transformation Matrix --> any format)
-        ###
-        print_header("Convert from Zivid (Rotation Matrix) to Robot")
-        axis_angle = rotation_matrix_to_axis_angle(rotation_matrix)
-        print(f"AxisAngle:\n{axis_angle.axis}, {axis_angle.angle:.4f}")
-        rotation_vector = rotation_matrix_to_rotation_vector(rotation_matrix)
-        print(f"Rotation Vector:\n{rotation_vector}")
-        quaternion = rotation_matrix_to_quaternion(rotation_matrix)
-        print(f"Quaternion:\n{quaternion}")
-        rpy_list = rotation_matrix_to_roll_pitch_yaw(rotation_matrix)
-
-        ###
-        # Convert from Robot to Zivid (any format --> Rotation Matrix (part of Transformation Matrix))
-        ###
-        print_header("Convert from Robot to Zivid (Rotation Matrix)")
-        rotation_matrix_from_axis_angle = axis_angle_to_rotation_matrix(axis_angle)
-        print(f"Rotation Matrix from Axis Angle:\n{rotation_matrix_from_axis_angle}")
-        rotation_matrix_from_rotation_vector = rotation_vector_to_rotation_matrix(rotation_vector)
-        print(f"Rotation Matrix from Rotation Vector:\n{rotation_matrix_from_rotation_vector}")
-        rotation_matrix_from_quaternion = quaternion_to_rotation_matrix(quaternion)
-        print(f"Rotation Matrix from Quaternion:\n{rotation_matrix_from_quaternion}")
-        roll_pitch_yaw_to_rotation_matrix(rpy_list)
-
-        # Replace rotation matrix in transformation matrix
-        transformation_matrix_from_quaternion = np.eye(4)
-        transformation_matrix_from_quaternion[:3, :3] = rotation_matrix_from_quaternion
-        transformation_matrix_from_quaternion[:-1, -1] = translation_vector
-        # Save transformation matrix which has passed through quaternion representation
-        assert_affine_matrix_and_save(
-            transformation_matrix_from_quaternion, Path(__file__).parent / "RobotTransformOut.yaml"
-        )
+    # Application class must be initialized before using other Zivid classes.
+    app = zivid.Application()  # noqa: F841  # pylint: disable=unused-variable
+
+    np.set_printoptions(precision=4, suppress=True)
+    print_header("This example shows conversions to/from Transformation Matrix")
+
+    transformation_matrix = load_and_assert_affine_matrix(get_sample_data_path() / "RobotTransform.yaml")
+    print(f"Transformation Matrix:\n{transformation_matrix}")
+
+    # Extract Rotation Matrix and Translation Vector from Transformation Matrix
+    rotation_matrix = transformation_matrix[:3, :3]
+    translation_vector = transformation_matrix[:-1, -1]
+    print(f"Rotation Matrix:\n{rotation_matrix}")
+    print(f"Translation Vector:\n{translation_vector}")
+
+    ###
+    # Convert from Zivid to Robot (Transformation Matrix --> any format)
+    ###
+    print_header("Convert from Zivid (Rotation Matrix) to Robot")
+    axis_angle = rotation_matrix_to_axis_angle(rotation_matrix)
+    print(f"AxisAngle:\n{axis_angle.axis}, {axis_angle.angle:.4f}")
+    rotation_vector = rotation_matrix_to_rotation_vector(rotation_matrix)
+    print(f"Rotation Vector:\n{rotation_vector}")
+    quaternion = rotation_matrix_to_quaternion(rotation_matrix)
+    print(f"Quaternion:\n{quaternion}")
+    rpy_list = rotation_matrix_to_roll_pitch_yaw(rotation_matrix)
+
+    ###
+    # Convert from Robot to Zivid (any format --> Rotation Matrix (part of Transformation Matrix))
+    ###
+    print_header("Convert from Robot to Zivid (Rotation Matrix)")
+    rotation_matrix_from_axis_angle = axis_angle_to_rotation_matrix(axis_angle)
+    print(f"Rotation Matrix from Axis Angle:\n{rotation_matrix_from_axis_angle}")
+    rotation_matrix_from_rotation_vector = rotation_vector_to_rotation_matrix(rotation_vector)
+    print(f"Rotation Matrix from Rotation Vector:\n{rotation_matrix_from_rotation_vector}")
+    rotation_matrix_from_quaternion = quaternion_to_rotation_matrix(quaternion)
+    print(f"Rotation Matrix from Quaternion:\n{rotation_matrix_from_quaternion}")
+    roll_pitch_yaw_to_rotation_matrix(rpy_list)
+
+    # Replace rotation matrix in transformation matrix
+    transformation_matrix_from_quaternion = np.eye(4)
+    transformation_matrix_from_quaternion[:3, :3] = rotation_matrix_from_quaternion
+    transformation_matrix_from_quaternion[:-1, -1] = translation_vector
+    # Save transformation matrix which has passed through quaternion representation
+    assert_affine_matrix_and_save(
+        transformation_matrix_from_quaternion, Path(__file__).parent / "RobotTransformOut.yaml"
+    )
 
 
 if __name__ == "__main__":